https://github.com/bioconductor-source/vidger

https://github.com/bioconductor-source/vidger

Repository

README.Rmd

---
output: github_document
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-"
)
```

# ViDGER 

[![Build Status](https://travis-ci.org/btmonier/vidger.svg?branch=master)](https://travis-ci.org/btmonier/vidger)
[![codecov](https://codecov.io/gh/btmonier/vidger/branch/master/graph/badge.svg)](https://codecov.io/gh/btmonier/vidger)
[![bioc](http://bioconductor.org/shields/downloads/release/vidger.svg)](https://bioconductor.org/packages/stats/bioc/vidger/) 
[![platforms](https://bioconductor.org/shields/availability/3.7/vidger.svg)](https://bioconductor.org/packages/release/bioc/html/vidger.html#archives)

## Overview
ViDGER (**Vi**sualization of **D**ifferential **G**ene **E**xpression 
using **R**), is an `R` package that can rapidly generate information-rich 
visualizations for the interpretation of differential gene expression 
results from three widely-used tools: `Cuffdiff`, `DESeq2`, and `edgeR`.


## Installation
The stable version of this package is available on 
[Bioconductor](http://bioconductor.org/packages/release/bioc/html/vidger.html)
. You can install it by:

```{r, eval=FALSE}
if (!require("BiocManager")) install.packages("BiocManager")
BiocManager::install("vidger")
```

If you want the latest version, install it directly from this GitHub repo:

```{r, eval=FALSE}
if (!require("devtools")) install.packages("devtools")
devtools::install_github("btmonier/vidger", ref = "devel")
```


## Functions
The stable release of `vidger` has 9 visualization functions:

* `vsScatterPlot()`
* `vsScatterMatrix()`
* `vsBoxplot()`
* `vsDEGMatrix()`
* `vsVolcano()`
* `vsVolcanoMatrix()`
* `vsMAPlot()`
* `vsMAMatrix()`
* `vsFourWay()`


## Loading test data
To simulate the usage of the three aformentioned tools, "toy" data sets have
been implemented in this package. Each of these data sets represents their
respective `R` class:

* `df.cuff` A `cuffdiff` output file.
* `df.deseq` A `DESeq2` object class.
* `df.edger` An `edgeR` object class.

To load these data sets, use the following command:

```{r, eval=FALSE}
data("")
```
...where `""` is one of the previously mentioned data sets.


## Getting help
For additional information on these functions, please see the given
documentation in the `vidger` package by adding the `?` help operator before 
any of the given functions in this package or by using the `help()` function. 

For a more in-depth analysis, consider reading the vignette provided with this 
package:

```{r, eval=FALSE}
vignette("vidger")
```

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*Last updated:* `r format(Sys.Date())`

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